Most anything that we would add to a solution and describe in a User Story is a process that has some sort of workflow. In most cases these workflows can be broken down into individual steps. A large User Story with several workflow steps can be broken down into smaller users stories based on these workflow steps.
Consider the following User Story for an ecommerce website.
As registered customer I want to purchase the items in my shopping cart so that my products can be delivered to an address I specify.
If we assume a fairly standard shopping cart and order entry process, we could identify the following steps:
As a registered customer I want to log in with my account so I don’t have to re-enter my personal information every time; As a registered customer I want to review and confirm my order, so I can correct mistakes on my order before I pay; As a registered customer I want to pay for my order with a credit card, so that I can confirm my order;
As a registered customer I want to pay for my order with a wire transfer, so that I can confirm my order;
As a registered customer I want to receive a confirmation e-mail with my order, so I have proof of my purchase;
As you see, there was more to this seemingly simple User Story than was originally apparent. By breaking the User Story down into its individual workflow steps and considering the different options that a user may use to pay we make the customers intentions much clearer to the developer implementing the functionality.
We must keep in mind the reason for creating User Stories in the first place; to engage the customer in conversation about desired functionality and clarify expectations before passing requirements on to the delivery team. The more granular our User Stories, the more specific our discussion of desired functionality and Acceptance Criteria can be.
Knowing the details of the workflow the team can prioritize the functionality based on business value. For example perhaps in the first release we only allow customers to pay with a credit card and we send the order confirmation manually or perhaps customers are required to enter their address information manually until saving addresses is available in release 2.
In any event having more granular user stories allows the delivery team to have detailed discussions about the desired functionality without missing key workflow steps or Acceptance Criteria.
In an Agile Development Project, the Solution Requirements are communicated from the customer to the delivery / development team using a standard notation easily understood by the delivery team and all stakeholders. This standard notation is known as a User Story. See our post on What Makes a Good User Story for more details.
When committing a User Story to a sprint in an agile project it is best that all the tasks necessary to take the User Story to the teams stated definition of done can be completed within a single sprint. In most cases a User Story so large that it cannot be completed within a sprint is a feature or epic that should be broken down into smaller components before being committed to the sprint.
There are several different ways we can go about breaking down or slicing a User Story. We call it slicing to invoke the “Layered Cake Metaphor”.
As the theory goes we can only truly enjoy our cake if we take a vertical slice of the cake ensuring that we get all of the flavors from each layer including the frosting between layers. Taking that concept to our layered application architecture this simply means that to really call a story “Done” we must be able to test and use the features introduced by the completion of the User Story. If we don’t get each layer of the application framework in our “slice” then we can’t use the feature. For example, a login feature is only useful if we have the login form at the user interface layer, some authentication logic at the business rules layer and data layer logic to compare the given username and password with values stored in a credential store. We need each layer of the cake to complete the story. If we only have the user interface layer we could enter the username and password but there would be nothing to compare it with. With this in mind “how” we slice our cake / User Stories is as important as the slicing itself.
The Test-Driven Development (TDD) Processes follows a pattern known as the TDD Rhythm which dictates the order in which elements of the solution should be created / edited.
Before we can successfully implement TDD a few key agile constructs must exist. Most importantly we must have Tasks derived from a User Stories (or requirements) that define the details of required system feature. These defined details would include the Acceptance Criteria for feature described in the User Story. We would then use the task details and acceptance criteria to define our tests.
The TDD Rhythm
1. Write a Failing Test
The first step in the TDD Rhythm is to Write a Failing Test. Using the Task Details, we write a test that exercises the functionality defined by the Users Story and expects that the value that is returned is the same as the value that is expected based on the Acceptance Criteria defined in the Task Details.
2. Run the Failing Test
Run the test to see it fail. This is an interesting step as depending on your application architecture may require some minimal project structure be created and project references made for your Failing Tests to even compile before they can run and fail. For example, if you are storing all of your Business Logic in a Class Library Project called BusinessRules that compiles as a Windows .dll and your Tests are centrally stored in a Test Project then your Class Library Project will have to Exist and the Namespace, Class and Method will have to exist before your Test Project will compile and the Tests will run and fail. Fortunately, Visual Studio includes code generation tools that will create the Classes and Methods as long as the Class Library Project Exists and at least one class with a Namespace statement exists. The Failing Test generated by Visual Studio will throw a NotImplementedException which will obviously cause the method to fail.
3. Write just enough code to pass the test
This can be a difficult concept to get your mind around for especially when the common simple TDD example code is used. For example, take a method simply returns a Boolean value to illustrate simple TDD method creation if we start with a test that runs the required Boolean method and expect the method to return a true the code to pass the test would simply be return True;
public void TestGetBool()
Figure A. Test Method to test GetBool Method
public static bool GetBool()
Figure B. Minimal code needed to pass the test
With this example it may seem like a waste of time to write this minimal code to pass the test as it is clear that the test needs a returned value of true in order to pass so where is the value is writing this useless passing test? Without writing the test that tests the “unhappy path” through our method (aka the test that expects a return value of false) it is hard to see the value is a method that simply returns true with no additional implementation logic. An eager developer may want to just skip to writing implementation logic without wasting time on the simplest code step of the TDD Rhythm but follow the pattern young Jedi. As seen in a slightly more complex method that returns a formatted string, understanding how the output should be formatted in order to pass the test can potentially be much more difficult than just returning a Boolean value of true.
public void TestWelcomeBack()
string expected = “Welcome Back Antoine! Your last visit to the site was 02/01/2016.”;
string actual = WebSite.BizRules.WelcomeBack(user);
string message = “We should get “ + expected;
Assert.AreEqual(expected, actual, message);
Figure C. Test Method to test WelcomeBack Method
public static string WelcomeBack(object user)
return “Welcome Back Antoine! Your last visit to the site was 02 / 01 / 2016.”;
Figure D. Minimal code needed to pass the test
In this example the Literal String returned including the user name Antoine and the last visit date would obviously need to be updated for each user and on each daily visit but the formatting and welcome statement may also be important and could possibly come from a configuration file somewhere. The point is that the minimal code required to pass the test in this case acts as documentation for the method including formatting requirements for returned values. On the next refactoring pass we would update the code in the method to include the code necessary to extract the user name from the user object passed to the method and retrieve the date of their last visit from the membership database and return it in the expected format. The String Literal is our formatting template as we create the implementation code we know what the expected result format looks like.
4. Run the Passing Test
At this point our method has just enough code to pass the test but does not necessarily meet the business requirement nor does it allow us to perform the task described by the user story. This will become obvious as more tests are developed to tests the “unhappy path” or as varying return values are expected by other tests. But at this point we understand what must be done for the test to pass and can keep that in mind as we refactor the code to make it meet the business requirement or for optimization purposes.
5. Refactor the Code
Depending on “minimal” code we wrote to pass the test our first refactoring pass may be to add required functionality or if the required functionality already exist we may be refactoring for Maintainability, Scalability or Performance Optimization. In any event as we refactor the code for whatever reason we can do so with the confidence that any changes that we make have tests in place to ensure that we have not made a change that would break existing functionality already passing tests. If you make a change and all of the sudden tests that were passing stop passing you know you have a problem. The tests can also be used for Gated Check-ins that require that any changes a developer makes to code must pass existing tests before it can be checked into Source Control allow bugs to be identified before they make into our build and potentially out to customers.
The Expanded TDD Rhythm
6. Run All Tests
Once we have refactored our code to include desired functionality or optimize for maintenance, scalability or performance we need to run all tests to ensure that our changes did not break the method that we were working on but also for any methods that depend on this method or its results. This is a necessary step to avoid failed check-ins on Source Control or Continuous Integration (CI) Servers where Gated Check-ins are used. With gated check-ins your check-in cannot break the automated build and all tests must pass or your check-in will be rejected and your code not allowed into source control until the issues are resolved.
As changes are required we can continue to repeat this process of writing failing tests, coding, passing tests and refactoring until our code for the features we are adding for our updates is “perfect”